Preprocessing - pathway data RoVI study — 03 May, 2023

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Sample summary

Unsupervised clustering

Session info

Sample summary

Basic statistics

Number of runs: 1
Number of samples (input count >0): 341
Number of controls: 0 3 samples with <1M reads after quality filtering in taxonomy module excluded (M001BS3, M077BS3, and M104BS3)

Sample type by country (includes replicates)

     
      India Malawi
  BS3   283     58

Minimum, median, and maximum output counts by country

  country         n       min       med       max
1   India     283.0  999999.0 1000000.0 1000000.9
2  Malawi      58.0  999999.2 1000000.0 1000000.7

Summary of input biom - ps1

  • n samples: 341
  • n features: 456
  • total reads (million): 341
  • mean % reads unmapped: NA
  • mean % reads unintegrated: NA
  • mean % reads mapped: NaN

No additional filtering required given that normalised pathway data (copies per million) serves as input.

Unsupervised clustering

Clustering of samples (columns) and pathways (rows) - presence/absence

Clustering of samples (columns) and pathways (rows) - scaled asin-sqrt transformed relative abundances

Heatmap with cluster assignments

Correlation structure of scaled asin-sqrt transformed relative abundances (Spearman’s rank)

Number of features: 456
Number of samples included: 341

Session info

R version 4.2.1 (2022-06-23)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur ... 10.16

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib

locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] Maaslin2_1.10.0        FSA_0.9.3              ALDEx2_1.28.1         
 [4] zCompositions_1.4.0-1  truncnorm_1.0-8        NADA_1.6-1.1          
 [7] survival_3.4-0         MASS_7.3-58.1          sjstats_0.18.1        
[10] ggExtra_0.10.0         formattable_0.2.1      inlmisc_0.5.5         
[13] wesanderson_0.3.6      phangorn_2.10.0        ape_5.6-2             
[16] DECIPHER_2.24.0        RSQLite_2.2.18         Biostrings_2.64.1     
[19] GenomeInfoDb_1.32.4    XVector_0.36.0         IRanges_2.30.1        
[22] S4Vectors_0.34.0       BiocGenerics_0.42.0    cowplot_1.1.1         
[25] scales_1.2.1           RVAideMemoire_0.9-81-2 DescTools_0.99.47     
[28] ggsignif_0.6.4         binom_1.1-1.1          shiny_1.7.3           
[31] randomcoloR_1.1.0.1    crossval_1.0.4         labdsv_2.0-1          
[34] mgcv_1.8-41            nlme_3.1-160           ggpubr_0.4.0          
[37] data.table_1.14.4      corrplot_0.92          vegan_2.6-4           
[40] lattice_0.20-45        permute_0.9-7          randomForest_4.7-1.1  
[43] matrixStats_0.62.0     lme4_1.1-30            Matrix_1.5-1          
[46] reshape2_1.4.4         pheatmap_1.0.12        DT_0.26               
[49] plotly_4.10.0          cluster_2.1.4          tidyr_1.2.1           
[52] dplyr_1.0.10           magrittr_2.0.3         plyr_1.8.7            
[55] kableExtra_1.3.4       gridExtra_2.3          RColorBrewer_1.1-3    
[58] knitr_1.40             ggplot2_3.3.6          phyloseq_1.40.0       

loaded via a namespace (and not attached):
  [1] estimability_1.4.1          coda_0.19-4                
  [3] bit64_4.0.5                 DelayedArray_0.22.0        
  [5] RCurl_1.98-1.9              generics_0.1.3             
  [7] terra_1.6-17                proxy_0.4-27               
  [9] bit_4.0.4                   webshot_0.5.4              
 [11] xml2_1.3.3                  httpuv_1.6.6               
 [13] SummarizedExperiment_1.26.1 assertthat_0.2.1           
 [15] xfun_0.34                   jquerylib_0.1.4            
 [17] evaluate_0.17               promises_1.2.0.1           
 [19] DEoptimR_1.0-11             fansi_1.0.3                
 [21] readxl_1.4.1                igraph_1.3.5               
 [23] DBI_1.1.3                   htmlwidgets_1.5.4          
 [25] purrr_0.3.5                 ellipsis_0.3.2             
 [27] backports_1.4.1             V8_4.2.1                   
 [29] insight_0.18.6              MatrixGenerics_1.8.1       
 [31] vctrs_0.5.0                 Biobase_2.56.0             
 [33] sjlabelled_1.2.0            abind_1.4-5                
 [35] cachem_1.0.6                withr_2.5.0                
 [37] robustbase_0.95-0           rgdal_1.5-32               
 [39] emmeans_1.8.2               getopt_1.20.3              
 [41] svglite_2.1.0               lazyeval_0.2.2             
 [43] crayon_1.5.2                flexdashboard_0.6.0        
 [45] pkgconfig_2.0.3             rlang_1.0.6                
 [47] lifecycle_1.0.3             miniUI_0.1.1.1             
 [49] modelr_0.1.9                cellranger_1.1.0           
 [51] datawizard_0.6.3            raster_3.6-3               
 [53] carData_3.0-5               lpsymphony_1.24.0          
 [55] Rhdf5lib_1.18.2             boot_1.3-28                
 [57] viridisLite_0.4.1           parameters_0.19.0          
 [59] rootSolve_1.8.2.3           bitops_1.0-7               
 [61] rhdf5filters_1.8.0          blob_1.2.3                 
 [63] stringr_1.4.1               rstatix_0.7.0              
 [65] memoise_2.0.1               zlibbioc_1.42.0            
 [67] compiler_4.2.1              cli_3.4.1                  
 [69] ade4_1.7-19                 tidyselect_1.2.0           
 [71] stringi_1.7.8               highr_0.9                  
 [73] yaml_2.3.6                  grid_4.2.1                 
 [75] sass_0.4.2                  fastmatch_1.1-3            
 [77] tools_4.2.1                 lmom_2.9                   
 [79] rstudioapi_0.14             foreach_1.5.2              
 [81] optparse_1.7.3              gld_2.6.6                  
 [83] farver_2.1.1                Rtsne_0.16                 
 [85] RcppZiggurat_0.1.6          digest_0.6.30              
 [87] quadprog_1.5-8              Rcpp_1.0.9                 
 [89] GenomicRanges_1.48.0        car_3.1-1                  
 [91] broom_1.0.1                 performance_0.10.0         
 [93] later_1.3.0                 httr_1.4.4                 
 [95] effectsize_0.8.1            colorspace_2.0-3           
 [97] rvest_1.0.3                 splines_4.2.1              
 [99] expm_0.999-6                sp_1.5-0                   
[101] multtest_2.52.0             Exact_3.2                  
[103] systemfonts_1.0.4           xtable_1.8-4               
[105] jsonlite_1.8.3              nloptr_2.0.3               
[107] Rfast_2.0.6                 R6_2.5.1                   
[109] pillar_1.8.1                htmltools_0.5.3            
[111] mime_0.12                   glue_1.6.2                 
[113] fastmap_1.1.0               minqa_1.2.5                
[115] BiocParallel_1.30.4         class_7.3-20               
[117] codetools_0.2-18            pcaPP_2.0-3                
[119] mvtnorm_1.1-3               utf8_1.2.2                 
[121] bslib_0.4.0                 tibble_3.1.8               
[123] curl_4.3.3                  biglm_0.9-2.1              
[125] rmarkdown_2.17              biomformat_1.24.0          
[127] munsell_0.5.0               e1071_1.7-12               
[129] rhdf5_2.40.0                GenomeInfoDbData_1.2.8     
[131] iterators_1.0.14            sjmisc_2.8.9               
[133] gtable_0.3.1                bayestestR_0.13.0          

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